Exploring the social and risk networks of male and female injection drug users in Toronto
Notice bibliographique
Résumé
Background. Injection drug users (IDUs) are at increased risk for contracting bloodborne infections. Individually focussed interventions have led to risk reductions but do not recognize that risk occurs within relationships. Network based interventions may add to harm reduction strategies that prevent the transmission of blood borne infections. To be able to develop effective interventions requires knowledge about IDUs' networks and the impact of networks on behaviour. Conclusions. While network-based prevention strategies may provide an additional level of harm reduction for injection drug users, programs should consider the differential impact of networks on male and female injection drug users and take these differences into consideration when designing effective strategies. Methods. A convenience sample of 150 IDU (75 males and 75 females) from the city of Toronto was interviewed in 2004. Participants were recruited through a number of sources and from across the city in an effort to include a diverse cross section. Respondents were asked a series of questions about themselves, their drug use and their risk behaviours. Drug, sex and support networks were elicited and questions about each contact were asked. Analyses at the participant level were logistic regression models that adjusted for confounding variables. Analysis at the level of the dyad involved hierarchical models that adjusted for data dependencies using generalized estimating equations with repeated measures corrections. Analyses were gender-stratified. Results. The analysis of network characteristics showed significant associations with risk participation, however male and female IDUs were not affected in the same way by their networks. While female IDUs rates of reporting participation in risk behaviours were affected by the inclusion of supportive, close drug relationships, male injectors seem to be most affected by the number of drug contacts that they had, their participation in the drug economy and their own levels of drug use. This suggests that women who inject drugs may be more readily influenced by their networks than male injectors. Objective. This thesis will describe the gender differences in the associations between egocentric network characteristics (size, multiplexity (relationship overlap), 'closeness') and injection risk behaviours (receptive needle sharing, sharing of injection paraphernalia and syringe mediated sharing).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».